jaidaken
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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
34 lines
1.2 KiB
Python
34 lines
1.2 KiB
Python
import os
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# Disable NPU device initialization and problematic MMCV ops to prevent RuntimeError
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os.environ['NPU_DEVICE_COUNT'] = '0'
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os.environ['MMCV_WITH_OPS'] = '0'
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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
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import comfy.model_management as model_management
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class Uniformer_SemSegPreprocessor:
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@classmethod
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def INPUT_TYPES(s):
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return define_preprocessor_inputs(resolution=INPUT.RESOLUTION())
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "semantic_segmentate"
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CATEGORY = "ControlNet Preprocessors/Semantic Segmentation"
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def semantic_segmentate(self, image, resolution=512):
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from custom_controlnet_aux.uniformer import UniformerSegmentor
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model = UniformerSegmentor.from_pretrained().to(model_management.get_torch_device())
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out = common_annotator_call(model, image, resolution=resolution)
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del model
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return (out, )
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NODE_CLASS_MAPPINGS = {
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"UniFormer-SemSegPreprocessor": Uniformer_SemSegPreprocessor,
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"SemSegPreprocessor": Uniformer_SemSegPreprocessor,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"UniFormer-SemSegPreprocessor": "UniFormer Segmentor",
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"SemSegPreprocessor": "Semantic Segmentor (legacy, alias for UniFormer)",
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} |